Deep learning enables machines to learn and solve complex problems using algorithms inspired by the human brain without any human intervention. Deep learning algorithms need data to learn, and lots of it! But that's no problem because we generate approximately 2.6 quintillion bytes a day1. Facial recognition uses images captured of an individual's face from photos or videos. The distances between the eyes, nose, mouth and jaw are measured.

Not if David Hanson has anything to do with it. The founder of Hanson Robotics, David has been dreaming of making sentient robots since childhood and while, for many of us, our childhood dreams never come true (I'm still waiting for my invite to become the sixth Spice Girl), Hanson's endless drive to push the field of robotics and AI further has meant that we're closer than ever to awakening consciousness in machines. To put it into context, Hanson is the mastermind behind the eerily lifelike robot Sophia, who uses sophisticated algorithms to track faces and engage in conversations with emotion. Quick witted enough to make Piers Morgan laugh on Good Morning Britain and win a game of rock, paper, scissors on The Tonight Show Starring Jimmy Fallon, Sophia's ability to socialise with humans might freak you out, but you can't deny it's impressive. In 2017, she also became the first robot to be granted citizenship to any country.

Artificial intelligence (AI), machine learning (ML) and continual deep learning (DL) are the new age digital skills that are being expected to transform the consumer and enterprise experience. Due to the vast amount of data that is now available in the Internet domain, machine learning and deep leaning have the capability to predict and prevent various catastrophically dangerous events. Now, Shell wants to leverage artificial intelligence to make petrol pumps a safer place. Shell has selected C3 IoT and Microsoft Azure to power a new companywide AI platform. A device inside petrol pumps running the Microsoft Azure IoT Edge can use artificial intelligence tools to pick out dangerous behavior like people lighting cigarettes while waiting at the pump, people driving recklessly, theft, and improper fueling.

WASHINGTON/SAN, FRANCISCO - Some of the biggest names in media and tech are gearing up to move into streaming in what could be a major challenge to market leader Netflix. Apple is expected to make its move with an announcement March 25 on its media plans, with a war chest estimated at some $1 billion and partners including stars like Jennifer Aniston and director J.J. Abrams involved in content. Walt Disney Co. has announced its new streaming service Disney will launch this year, as will another from WarnerMedia, the newly acquired media-entertainment division of AT&T. The new entrants, with more expected, could launch a formidable challenge to Netflix, which has some 140 million paid subscribers in 190 markets, and to other services such as Amazon and Hulu. "It's really going to change the industry," said Alan Wolk, co-founder of the consulting firm TVREV who follows the sector.

Manufacturing sites worldwide use industrial robots to streamline and automate operations. Japan has led the world in industrial robot technology, and now is about to spur an even greater evolution by combining this technology with an open source deep learning framework developed in Japan. Deep learning enables industrial robots to make judgments in complex operational situations by learning from past examples. Moreover, the learning can be shared between robots to increase efficiency. Watch this video to learn how this innovative approach will deliver previously unavailable levels of advanced automation in manufacturing.

A new federal commission on artificial intelligence is being led by Democrats. The National Security Commission on Artificial Intelligence (AI), a federally appointed commission, held its first meeting Monday chaired by former Google executive and billionaire Eric Schmidt, a major donor and informal adviser to former President Barack Obama. The commission's vice chairman is Robert Work, who was deputy defense secretary in the Obama administration. Additionally, the AI commission has hired as a staff member Ylli Bajraktari, a former National Security Council staff member under Mr. Obama. Mr. Bajraktari also was a former aide to Obama Defense Secretary Ash Carter.

If an automated car had to choose between crashing into a barrier, killing its three female passengers, or running over one child in the street -- which call should it make? When three U.S.-based researchers started thinking about the future of self-driving cars, they wondered how these vehicles should make the tough ethical decisions that humans usually make instinctively. The idea prompted Jean-François Bonnefon, Azim Shariff, and Iyad Rahwan to design an online quiz called The Moral Machine. Would you run over a man or a woman? By 2069, autonomous vehicles could be the greatest disruptor to transport since the Model T Ford was launched in Detroit in 1908.

If you shop on Amazon, an algorithm rather than a human probably set the price of the service or item you bought. Pricing algorithms have become ubiquitous in online retail as automated systems have grown increasingly affordable and easy to implement. But while companies like airlines and hotels have long used machines to set their prices, pricing systems have evolved. They have moved from rule-based programs to reinforcement-learning ones, where the logic of deciding a product's price is no longer within a human's control. If you recall, reinforcement learning is a subset of machine learning that uses penalties and rewards to incentivize an AI agent toward a specific goal.

Should we be scared of artificial intelligence (AI)? Some notable individuals such as legendary physicist Stephen Hawking and Tesla and SpaceX leader and innovator Elon Musk suggest AI could potentially be very dangerous; Musk at one point was comparing AI to the dangers of the dictator of North Korea. Microsoft co-founder Bill Gates also believes there's reason to be cautious, but that the good can outweigh the bad if managed properly. Since recent developments have made super-intelligent machines possible much sooner than initially thought, the time is now to determine what dangers artificial intelligence poses. What is applied and general artificial intelligence?

Machine learning has the potential to democratize access to credit. It can expand the pool of people qualified to obtain credit -- most notably low- and moderate-income (LMI) borrowers -- and decrease the cost of that credit. It also can increase access to credit and reduce systemic risk by allowing different banks to analyze different factors, and thereby generate different results in a way that the existing, FICO-based system discourages. The greatest current obstacle to this development is pressure from the banking regulators to continue adhering to the status quo system, lest machine learning produce an unfortunate outcome. Perversely, that system already contains the very flaws that regulators have expressed about machine learning.